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Adaptive Unsupervised Multi-view Feature Selection for Visual Concept Recognition
[chapter]
2013
Lecture Notes in Computer Science
To reveal and leverage the correlated and complemental information between different views, a great amount of multi-view learning algorithms have been proposed in recent years. However, unsupervised feature selection in multiview learning is still a challenge due to lack of data labels that could be utilized to select the discriminative features. Moreover, most of the traditional feature selection methods are developed for the single-view data, and are not directly applicable to the multi-view
doi:10.1007/978-3-642-37331-2_26
fatcat:4qumx6p6qrhutihtdb4f7q3gbi